Abbas, A.

Aguerre, V.

Albín, A.

Casagrande, M.

Chilibroste, P.

Claassen, F.

Dogliotti, S.

Groot, J.C.J.

Rossing, W.A.H.

English

Wageningen Yield 

1er Congreso en Co-Innovación de Sistemas Sostenibles de Sustento Rural 
 159 
SUSTAINABLE FUTURES FOR VEGETABLE FAMILY FARMERS IN 
URUGUAY: A MODEL-BASED EXPLORATION 
 
M. Casagrandea, S. Dogliottib, J. Groota, V. Aguerrec, A. Abbasa, A. Albínc, F. Claassend, P. 
Chilibrosteb and W. Rossinga 
aBiological Farming Systems Group, Wageningen University, The Netherlands, bFacultad de 
Agronomía, Montevideo, Uruguay, cINIA, Instituto Nacional de Investigación Agropecuaria, 
Canelones, Uruguay, dOperations Research and Logistics Group, Wageningen University, 
Wageningen, The Netherlands 
marion.casagrande@wur.nl, 
 
INTRODUCTION 
In a context of continued decreasing product prices on the internal market and increasing costs 
of inputs over the past 20 years, vegetable family farms in Uruguay have been intensifying and 
specializing their production systems, putting more pressure on already deteriorated soils and on 
limited farm resources. Researchers from the Faculty of Agronomy in Montevideo, later joined by 
Wageningen University, started a series of learning cycles in order to identify alternative options for 
vegetable growers in Southern Uruguay. A first extended learning cycle comprised one-year long 
interactions of many generations of students of the Faculty of Agronomy with farm families that 
helped developing relations between the farmers and the Faculty. A next cycle was completed by 
Dogliotti et al. (2005), involving a formal model-based diagnosis of the problems in the farms, and an 
assessment of alternatives. Existing and potential farming systems for a number of selected farms were 
evaluated in terms of objectives thought relevant for the farmers, including environmental objectives 
(soil fertility, exposure to pesticides, nutrients balances) and social-economic objectives (family 
income, gross margin, labor availability). The results showed great promise for ecological-economic 
win-win situations if farmers would drastically alter their strategies and base them on wider rotations, 
fewer crops and use of (green) manure. These results constituted the hypotheses to be tested during a 
third learning cycle, which was implemented during the EULACIAS20 project. In this project 16 farms 
were diagnosed and redesigned in very close interaction with the farm family and the most promising 
farm strategy was tested in the farmer practice. Positive results were found after 2-3 years of 
interaction with most farmers.  
Next objective was to extend the study and get results not only for the pilot farms but also at 
regional scale that could inform regional policy, farmer union activities and the research agenda. A 
regional farm typology was combined with a set of scenarios in a model-based exploration of 
development options for each of the farm types. Here we describe the approach and present 
preliminary results of the exploration of options for a real farm belonging to one of the two most 
abundant farm types. Ultimate goal is to contribute to construction of policies that foster sustainable 
family farming in Southern Uruguay. 
 
MATERIAL AND METHODS 
Study area, farm typology and scenarios 
The study area was located in the temperate region of Canelones, South Uruguay, which 
concentrates more than 50% of the vegetable producers of the country. The main structural problems 
of horticultural farms in the area are (i) deteriorated soil quality, (ii) high incidence of soil erosion, (iii) 
limited surfaces of productive areas, (iv) insufficient irrigation water. Availability of off-farm labor is 
becoming a problem in the region and experts predict that it will be increasingly scarce and expensive. 
Seven representative types of vegetable production farms were identified in the region using a 
                                                 
20
 EU FP6-2004-INCO-dev-3; contract nr 032387 ; http://www.eulacias.org/ 
M. Casagrande et al. 
 160
quantitative typology method based on cluster analysis, multidimensional scaling and similarity 
percentages analysis (Righi et al., 2009). The types differed in use of off-farm labor, mechanization 
endowment and irrigation potential. Three scenarios of major agricultural changes concerning social 
and economic regional drivers for a time horizon of 10 years were defined by local experts using 
Delphi methods (Contini et al., 2010): an ‘organic’, a ‘supply chain’ and a ‘conventional’ scenario. 
Scenarios were associated with optimistic and pessimistic trends in prices of products and inputs, 
resulting in 6 scenario-trend combinations. 
Modeling toolkit 
Based on the previous work of Dogliotti et al. (2003, 2004, 2005) a modeling toolkit was 
developed to explore the effect of scenarios and farm endowment on the design and assessment of new 
farming systems. This toolkit was divided into two components: (i) one that generates and evaluates 
production activities at field level and (ii) another one that selects combinations of production activities 
at farm level to reveal trade-offs between environmental and social-economic objective functions 
based on interactive multiple goal linear programming (IMGLP) (Fig. 1). At field scale, generation of 
crop rotations was based on ROTAT (Dogliotti et al., 2003) and rotations were later combined with 
management levels (e.g. irrigation) to create what are denoted ‘production activities’. Each production 
activity was then evaluated with sustainability indicators that represent economic (labor requirements, 
production costs, gross margin) and environmental (nutrient balances, evolution of soil organic matter 
balance, evolution of erosion21, exposure to pesticides) considerations. At farm scale, an ‘optimal’ 
combination of production activities was selected with an improved and extended version Farm 
Images model (Dogliotti et al., 2005), revealing trade-offs among multiple objectives that are subject 
to internal and external constraints (Fig. 1). Social-economic objective functions at farm-scale were 
gross margin ($U.yr-1), family income ($U.yr-1), capital requirements ($U.yr-1) and ‘family labor use’ 
(i.e. ratio of family labor hours used over the total family labor hours available). Environmental 
objective functions were Environment Exposure to Pesticides (EEP) for soil (kg-days.yr-1), N surplus 
(kg.ha-1.yr-1), erosion (Mg.ha-1.yr-1) and soil organic matter (SOM) balance (kg. ha-1.yr-1). 
Case study farm 
We studied a farm specialized in vegetable crops, belonging to the largest farm category of the 
region, characterized by a small area of Typical Argiudoll soil (3.2 ha), a comparatively low supply of 
irrigation water (1.5 ha) and a low mechanization level. The modeling toolkit was used to explore 
options for sustainable farming systems for each scenario-trend combination. At field level, agronomic 
criteria for generating rotations were scenario dependant; intercrops were used to improve soil quality. 
Rotations included irrigated and rain-fed crops according to three levels of irrigation (none, 
intermediate and high). At farm level, for each scenario-trend combination we performed 3 
optimization rounds, with different values for constraints, where we optimized the 8 objective 
functions one by one. For the third round, minimum family labor use was set to 50%, minimum family 
income was set to the current income of the farm (187000 U$.yr-1) and minimum soil erosion was set 
respectively to 5, 6.5 and 7 Mg.ha-1.yr-1 for ‘supply chain’, ‘organic’ and ‘conventional’ scenarios, to 
reduce soil erosion compared with current conditions. Results presented below are the selected 
production activities of the third round when maximizing family income. 
RESULTS AND DISCUSSION 
Field level Results  
At field scale, the ROTAT model generated 2800, 3495 and 9147 rotations for ‘conventional’, 
‘organic’ and ‘supply chain’ scenarios, respectively. After applying the three possible levels of 
irrigation, 5672, 7048 and 19734 productions activities were created for the ‘conventional’, ‘organic’ 
                                                 
21
 In this preliminary study, erosion was overestimated by about 14% for rotations including alfalfa because we did not take 
into account its root biomass in the calculations. 
1er Congreso en Co-Innovación de Sistemas Sostenibles de Sustento Rural 
 161 
and ‘supply chain’ scenarios, respectively. The higher number of rotations and production activities for the ‘supply 
chain’ scenario is mainly due to a higher diversity of candidate crops compared to the ‘conventional’ scenario and 
higher crop frequencies allowed in the rotations compared to the ‘organic’ scenario. Economic indicators (family 
income and gross margin) always showed higher values for production activities associated with irrigation (either 
intermediate or high level of irrigation), whatever the scenario and trend studied. Under an optimistic price trend, 
production activities without irrigation were not reaching gross margin over 70,000 $U.ha-1.yr-1, whatever the scenario 
while irrigated rotations could reach more than 250,000 $U.ha-1.yr-1.  
Farm level Results  
At farm scale, either 2 or 3 production activities were found to optimize family income while respecting 
environmental and farm endowment constraints for each scenario-trend combination (Tab. 1). They were associated 
either with intermediate or high level of irrigation, which positively contributed to economic performance compared to 
no irrigation. Moreover, for each scenario tomato was cropped and this crop is related to higher gross margins. Thus, 
IMGLP selected those production activities which had higher economic performances. In case of ‘organic’ and ‘supply 
chain’ scenarios, production activities selected and their areas were exactly the same for the two price trends. As a result 
environmental performances were the same for both trends, while economic performances of pessimistic trend were 
naturally lower than optimistic trend (Tab. 1). In case of the ‘conventional’ scenario 2 out of 3 selected production 
activities were the same for both trends. The third production activity differed for one crop from one trend to the other. 
This showed that whatever the trend, the combination of production activities leading to the best trade-off between 
environmental and economic performances would be similar for a given scenario.  
The extrapolated value of current family income in rural areas of this region for a time horizon of 10 years was 
estimated to be 328,337 $U yr-1, an increase of 50% compared to the current level. The ‘Conventional’ scenario was the 
only scenario to reach this value for both trends and was the most desirable scenario in terms of family income (Tab. 1). 
According to local experts labor price is expected to be 55 $U.hr-1 in 10 years. For all scenarios, labor productivity could 
reach this value but in the ‘organic’ scenario, with a pessimistic price trend, labor productivity was only 66 $U.hr-1 (Tab. 
1), meaning that 11 $U.hr-1 should be enough to cover entrepreneurship of the farmer. The ‘Supply chain’ scenario was 
the most desirable in terms of labor productivity while requiring low capital compared with ‘conventional’ scenario and 
involving the lowest erosion rate (Tab.1). Heading towards such a future thus seems to be interesting for the type of 
specialized vegetable farm studied from an economic-environmental perspective. However, the ‘supply chain’ scenario 
implies contracts with industry that could be difficult to get. In this study, the ‘organic’ scenario does not seem the most 
desirable both regarding economic and environmental performances (Tab. 1). Environment exposure to pesticides 
(EEP) for soil reached high values especially for the ‘organic’ scenario because of the widespread use of mineral 
pesticides such as Bordeaux mixture (Tab. 1). Moreover the minimum value for EEP set in the optimization process 
constrained family income for each scenario. In order to increase income we could (i) release the constraint on EEP and 
accept more environmental impact and/or (ii) develop cropping practices using less mineral pesticides to get lower EEP 
values at farm scale. 
This study offered the opportunity to develop a flexible modeling toolkit that could be usable for other research 
studies while providing information to farmers and policy makers about sustainable futures in the study region. 
 
REFERENCES 
Contini C., Gabbai M., Omodei Zorini L., B. Pugh, 2010. Involving stakeholders in the exploration of sustainability 
perspectives and innovations of farming systems: a case study from Latin America. Presentation held at the 9th 
European Symposium of the International Farming Systems Association in Vienna, Austria, 4-7 July 2010. 
Dogliotti, S., Rossing, W.A.H., M.K. Van Ittersum, 2003. ROTAT, a tool for systematically generating crop rotations. 
European Journal of Agronomy 19: 239-250. 
Dogliotti, S., Rossing, W.A.H., M.K. Van Ittersum, 2004. Systematic design and evaluation of crop rotations enhancing 
soil conservation, soil fertility and farm income: a case study for vegetable farms. Agricultural Systems 80: 277-
302. 
Dogliotti, S., Van Ittersum, M.K., W.A.H. Rossing, 2005. A method for exploring sustainable development options at 
farm scale: a case study for vegetable farms. Agricultural Systems 86: 29-51. 
M. Casagrande et al. 
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Righi, E., Pacini G.C., Dogliotti S., Aguerre V., W.A.H. Rossing, 2009. Farm typology identification by multi-variate 
analysis as a method to scale-up results of integrated impact assessment. Presentation held at the AgSAP 
Conference in Egmond aan Zee, The Netherlands, 10-12 March 2009. 
Wijnands F.G., 1997. Integrated crop protection and environmental exposure to pesticides: methods to reduce use and 
impact of pesticides in arable farming. European Journal of Agronomy 7: 251-260. 
Promising
FARM
SYSTEM
Promising
FARM
SYSTEM
Promising
FARM
SYSTEM
Promising
FARM
SYSTEM
SCENARIOS Trend
CROPS
ROTAT
Model
Agronomic
filters
Crop Protection
Level
Animal
Production
Intercrop
Management
CROP 
ROTATIONS
CROP ROTATIONS
MANAGEMENT
SYSTEMS
CROP 
MANAGEMENT
SYSTEMS
PRODUCTION 
ACTIVITIES
Input-Output 
Tables
Physical 
Environment
IMGLP
Model
Constraints
Objective 
Functions
Field 
evaluation
Soil quality,
area
Farm 
resources
Labor, capital, 
water, 
animal feeding
Promising
FARM
SYSTEM
Mechanization
Level
FIELD LEVEL
Design of Production Activities
FARM LEVEL
Design of Farm Systems
Irrigation
Level
 
 
Figure 1. Overview of the modeling toolkit 
Table 1. Selected production activities and their economic and environmental performances for the ‘organic’, 
‘conventional’ and ‘supply chain’ scenarios. 
 Organic Conventional Supply chain 
 Optimistic Pessimistic Optimistic Pessimistic Optimistic Pessimistic 
Number of selected production 
activities 2 2 3 3 2 2 
Rotation length (yr) 7 and 8 7 and 8 6 6 6 6 
Number of crops on the farm 9 9 5 5 5 5 
Area used (ha) 2.0 2.0 3.2 3.0 3.0 3.0 
Irrigated area (ha) 1.2 1.2 1.5 1.5 1.0 1.0 
Family income ($U.yr-1) 295,391  191,576  457,421  417,991  290,982  218,109  
Capital requirements ($U.yr-1) 193,092  221,755  263,457  302,886  179,312  211,290  
Farm production costs ($U.yr-1) 170,897  199,560  198,785  237,379  157,117  189,095  
Return to assets ($U.yr-1)1 194,408  90,593  190,102  183,088  212,987  140,114  
Family labor use (-) 0.7 0.7 0.8 0.8 0.6 0.6 
Labor productivity ($U.hr-1) 102  66  95  92  117  88  
EEP soil (kg-day.yr-1)2 150000 150000 100000 100000 100000 100000 
EEP water (ppm.yr-1)2 894 894 5306 5306 5298 5298 
EEP air (kgAI.ha-1.yr-1)2 0.2 0.2 7.1 7.1 6.7 6.7 
N surplus (kg.ha-1.yr-1) 46.6 46.6 53.0 53.0 70.4 70.4 
Erosion (Mg.ha-1.yr-1) 6.5 6.5 7.0 7.0 4.6 4.6 
SOM (kg.ha-1.yr-1) 744.3 744.3 570.9 570.9 340.2 340.2 
1
 Return to assets (land, own capital and management of farm) is defined as the gross margin minus the costs of 
hired and own labor 
2
 Environment exposure to pesticides for soil, water and air refers to the indicators of Wijnands (1997) 


A method for exploring sustainable development options at farm scale: a case study for vegetable farms.

Farm typology identification by multi-variate analysis as a method to scale-up results of integrated impact assessment.

Integrated crop protection and environmental exposure to pesticides: methods to reduce use and impact of pesticides in arable farming.

Involving stakeholders in the exploration of sustainability perspectives and innovations of farming systems: a case study from Latin America.

ROTAT, a tool for systematically generating crop rotations.

Systematic design and evaluation of crop rotations enhancing soil conservation, soil fertility and farm income: a case study for vegetable farms.

Sustainable futures for vegetable family farmers in Uruguay: a model-based exploration

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Sustainable futures for vegetable family farmers in Uruguay: a model-based exploration

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